A high resolution line list for AlO

Indications of aluminium monoxide in atmospheres of exoplanets are being reported. Studies using high resolution spectroscopy should allow a strong detection but require high accuracy laboratory data. A Marvel (measured active rotational-vibrational energy levels) analysis is performed for the available spectroscopic data on 27Al16O: 22 473 validated transitions are used to determine 6 485 distinct energy levels. These empirical energy levels are used to provide an improved, spectroscopically accurate version of the ExoMol ATP line list for 27Al16O; at the same time the accuracy of the line lists for the isotopically-substituted species 26Al16O, 27Al17O and 27Al18O are improved by correcting levels in line with the corrections used for 27Al16O. These line lists are available from the ExoMol database at http://www.exomol.com.

Bayesian back-calculation and nowcasting for line list data during the COVID-19 pandemic

Surveillance is critical to mounting an appropriate and effective response to pandemics. However, aggregated case report data suffers from reporting delays and can lead to misleading inferences. Different from aggregated case report data, line list data is a table contains individual features such as dates of symptom onset and reporting for each reported case and a good source for modeling delays. Current methods for modeling reporting delays are not particularly appropriate for line list data, which typically has missing symptom onset dates that are non-ignorable for modeling reporting delays. In this paper, we develop a Bayesian approach that dynamically integrates imputation and estimation for line list data. Specifically, this Bayesian approach can accurately estimate the epidemic curve and instantaneous reproduction numbers, even with most symptom onset dates missing. The Bayesian approach is also robust to deviations from model assumptions, such as changes in the reporting delay distribution or incorrect specification of the maximum reporting delay. We apply the Bayesian approach to COVID-19 line list data in Massachusetts and find the reproduction number estimates correspond more closely to the control measures than the estimates based on the reported curve.